CN109507749A - A kind of heavy magnetic is from constraint 3-d inversion and joint interpretation method - Google Patents
A kind of heavy magnetic is from constraint 3-d inversion and joint interpretation method Download PDFInfo
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Abstract
The invention discloses a kind of heavy magnetic to constrain 3-d inversion and joint interpretation method certainly, comprising the following steps: carrying out sliding-model control cutting to the underground space of objective area first is multiple grid cells；It calculates separately each grid cell and the constraint nuclear matrix certainly of gravity and magnetic method inverting is respectively formed using corresponding MIC value and depth weighted coefficient as from constraint function for the MIC value of gravity and magnetic method data；Gravity and magnetic method inversion problem are solved respectively by LSQR method, obtain the inversion result of gravity and magnetic method；According to gravity and magnetic method inversion result, the density and magnetism of each grid cell are calculated；The MIC value between the density and magnetism on depth direction is calculated again, and analysis and geologic interpretation are carried out according to the planar distribution of MIC value.The present invention can promote the reliability of inversion result and save Inversion Calculation cost, and quickly carry out joint interpretation.
Description
Technical field
The invention belongs to technical field of geological exploration, and in particular to a kind of heavy magnetic is from constraint 3-d inversion and joint interpretation side
Method.
Background technique
Latent Deep Geological Structures mineral resources, petroleum gas are reconnoitred and large-scale construction project etc. all
Have great importance.Gravity-Magnetic Survey data have certain Deep Information, close according to Gravity-Magnetic Survey data acquisition subsurface three-dimensional
Degree and magnetic, to explain and divide to geological structure, for three-dimensional geological modeling and transparence, predicting oil/gas resource and
The position and preservation space of deep orebody, large-scale construction project addressing etc. are all particularly important.
Weight magnetic inverting is exactly the density and magnetism according to the observation data acquisition underground space.Wherein, inversion for physical properties is by underground
Spatial spreading is several grid cells, only solves the corresponding density of each unit or magnetism, it is easy to simulate complicated geologic body,
Important directions as 3-d inversion.Currently, weight magnetic three-dimensional inversion for physical properties is primarily present the problem of two aspects: first, inverting
Discrete ill-posed problem can be attributed to, multi-solution and unstability are serious；Second, with the increase of observation data volume, phase therewith
The calculation amount answered increases in geometry grade, and it is huge to calculate cost.In addition, how to be carried out quickly after obtaining ground lower density and magnetism
Joint interpretation and one of urgent problem.
Around the above problem, domestic and foreign scholars have done a large amount of correlative studys.In the nonuniqueness for reducing solution and improve solution
In terms of stability, it is based primarily upon Tikhonov regularization and solves ill-posed problem, and believed as much as possible using priori in inverting
Breath applies constraint to solution model, and the potential information for including using potential field itself carries out from constraint inverting etc. solution model, but
Tikhonov regularization is related to computationally intensive, and need to explicitly store large-scale dense nuclear matrix, and it is big to calculate cost.It is saving
It is calculated as present aspect, mainly there is parallel computation, nuclear matrix compression and the methods of reconstruct, quick forward modelling.In density and magnetism
It in terms of joint interpretation, is usually cut into many sections and explains, this way is no doubt effective, but unquestionable is corresponding
Workload can be very big.
Summary of the invention
In order to solve the above problems existing in the present technology, it is three-dimensional anti-from constraining that it is an object of that present invention to provide a kind of heavy magnetic
It drills and joint interpretation method.
The technical scheme adopted by the invention is as follows: a kind of heavy magnetic from constraint 3-d inversion and joint interpretation method, including with
Lower step:
G1. carrying out sliding-model control cutting to the underground space of objective area first is multiple grid cells；
G2. each grid cell is calculated separately for the MIC value of gravity and magnetic method data, by corresponding MIC value and depth
Weighting coefficient is used as from constraint function, is respectively formed the constraint nuclear matrix certainly of gravity and magnetic method inverting；
G3. gravity and magnetic method inversion problem are solved by regularization method respectively, obtain the inversion result of gravity and magnetic method；
G4. according to gravity and magnetic method inversion result, the density and magnetism of each grid cell are calculated；
G5. the MIC value between the density and magnetism on depth direction is calculated again, and is advised according to the plane distribution of MIC value
Rule carries out analysis and geologic interpretation.
Further, because the underground space of objective area is divided into multiple grid cells in the step G2, therefore inverting mould
Type is as follows:
Am=d
In formula: A is nuclear matrix；M is vector to be solved, i.e. density or magnetism；D is observation data vector.
The ill-posedness of inverting is shown: nuclear matrix is unusual and ill；Observation data are inevitably present error
Deng.So that the direct solution of above formula is not unique and unstable, this just needs special method for solving, i.e. regularization method.Currently, solving
The regularization method of ill-posed problem can be divided into direct regularization (such as: Tikhonov) and Iteration Regularized (such as: LSQR).
Further, as follows from constraint function expression formula in the step G2:
D=DMICDdepth
In formula: the DMIC=diag { 1/MIC1,1/MIC2,Λ,1/MICM, and MICjFor corresponding grid cell
MIC value；The Ddepth=diag { 1/ (z1)β/2,1/(z2)β/2,Λ,1/(zM)β/2, zjThe center of as corresponding grid cell
Buried depth.
Wherein, the expression formula of depth weighted function is as follows:
Ddepth=diag { 1/ (z1)β/2,1/(z2)β/2,Λ,1/(zM)β/2}
In formula: the DdepthFor about depth from constraint function；And zjFor the center buried depth of corresponding unit.
Further, the inverse model in the step G2 is as follows:
A*m*=d
In formula: the A*=AD-1；The m*=Dm.
Further, it is calculated in the step G3 using LSQR canonical algorithm.
Currently, the D inversion of gravity and magnetic anomalies overwhelming majority is all based on Tikhonov regularization.It is three-dimensional for the heavy magnetic of big data quantity
For inverting, Tikhonov regularization can expend a large amount of calculating cost, and be mainly manifested in: every Inversion Calculation is primary, all needs to count
Calculate transposition, the sum of products matrix inversion of multi-degree matrix etc. of matrix；Every inverting iteration is primary, all needs by repeatedly calculating selection most
Good regularization parameter, and the calculating of each regularization parameter is equivalent to an Inversion Calculation；It need to explicitly store large-scale dense
Nuclear matrix.
LSQR method is that one kind effectively way of large linear systems problem is to solve for based on Krylov-subspace projection method
Diameter, while it has natural regularization property again, the number of iterations is regularization parameter, is had to calculator memory requirement
The advantages that low, iteration convergence is fast and solving result is stablized.Hilber, Pascal matrix and seismic tomography numerical experiment knot
Fruit shows that LSQR method is reliable and stable compared with Tikhonov regularization.Therefore, ill-posed problem is solved using LSQR method, solves and thinks
Road is that Arbitrary Coefficient matrix equation is turned to the equation that coefficient matrix is square matrix first, then utilizes Lanczos method, solution side
The least square solution of journey.Weight magnetic indirect problem is solved using LSQR method, mainly there is the characteristics of following two aspect:
1) when inverting only the solving result of the number of iterations corresponding to inflection point need to be returned, is avoided according to the inflection point of L-curve
Regularization parameter selection and the calculating cost of extra consumption；
2) LSQR algorithm relates only to the product of matrix and vector, and large-scale dense nuclear matrix can not have to explicit represent
Come, this is advantageous the D inversion of gravity and magnetic anomalies of big data quantity；
Further, specific step is as follows by the step G2-G4:
Nuclear matrix elements A (i, j) and MIC are calculated firstj；
Then constraint nuclear matrix A is calculated*, according to A*(i, j)=A (i, j) ljA is calculated*, wherein
Discomfort, which is solved, based on LSQR algorithm determines A*m*=d, according to according to L-curveTurn
Point returns to the solution of corresponding the number of iterations；
Grid cell circulation, according to formulaReverse model value, exports solving result m, and inverting terminates.
Here MIC coefficient is introduced, because inverting has multi-solution and unstability, to the greatest extent may be used in inverting from constraining
Energy ground, which applies solution model using prior information (including geology, drilling and seismic data etc.), to be constrained, and solution may make more to accord with
Actual conditions are closed, but in some cases, prior information is simultaneously inadequate.Paoletti etc. points out that include using field source itself dives
Solution model is carried out in information the reliability of inversion result can be improved from constraining.In fact, the grid list of underground space discretization
For member with observation data there are certain correlation, correlation is stronger, shows that the unit is bigger to the contribution possibility of observation data, because
This is weighted constraint to grid cell using correlation coefficient value.
Defined by MIC it is found that some grid cell and observation data between MIC value it is bigger, indicate the grid cell with
The correlation for observing data is stronger, that is to say, that and the grid cell is bigger to the contribution possibility of gravity-magnetic anomaly, when inverting, the net
The weight of lattice unit is also bigger accordingly, to be carried out using MIC from constraint.It is written as
DMIC=diag { 1/MIC1,1/MIC2,Λ,1/MICM}
In view of potential field " skin effect ", enable from constraint function
D=DMICDdepth
In formula: Ddepth=diag { 1/ (z1)β/2,1/(z2)β/2,Λ,1/(zM)β/2, zjFor corresponding unit center buried depth.
Due to being diagonal matrix from constraint matrix D, there is D-1D=I (I is unit matrix), then Am=d formula is writeable are as follows:
AD-1Dm=d
Enable A*=AD-1, m*=Dm, has:
A*m*=d
Matrix A in above formula*Different from nuclear matrix A, it is contained from constraint information, i.e., from constraint nuclear matrix, undoubtedly makes
It is more abundant to obtain information, helps to improve the reliability of inversion result.
At this point, solving A using Iteration Regularized method LSQR method*m*=d, and returned according to the inflection point of L-curve and solve knot
Fruit m*, further according to formula m=D-1m*Reverse model value has given up traditional Tikhonov regularization, saves a large amount of calculating costs.
Further, specific step is as follows by the step G5:
(5.1) according to each horizontal grid unit of weight magnetic inverting, its density and magnetism on depth direction is taken, is calculated
MIC value；
(5.2) finally using the plane coordinates of horizontal grid unit and MIC value at figure, geologic body and rift structure are divided.
The information content that D inversion of gravity and magnetic anomalies result provides is much larger compared to two dimensional inversion, in density and magnetic joint interpretation side
Face is conventionally cut into more sections and explains and no doubt proves effective, but unquestionable is that corresponding workload also can
It is very big.As can effective extract and excavate potential information between two attribute data, it is possible to provide interpretation mark more abundant,
Efficiency that is close and improving joint interpretation.
In general, main rock and the density on stratum and magnetic performance are stronger correlation, as sedimentary rock is (low close
Degree, low magnetism), granite (low-density, low magnetism), gold-bearing property (high density, high magnetic) etc.；And fracture belt then due to
Rock is relatively broken often to show as low-density, magnetic then increase without significant change or because of Extract Mineralized Alteration, that is to say, that
The density of fracture belt and magnetic correlation are weak or uncorrelated.Therefore it can use this correlativity as division geologic body and break
One of mark split.
Specific practice are as follows: according to each horizontal grid unit of weight magnetic inverting, take its density and magnetic on depth direction
Property, MIC value between the two is calculated, then according to the plane coordinates of horizontal grid unit and MIC value at figure, to divide geologic body
And rift structure.When geologic body is not subject to obvious bad break, MIC value is larger and uniform；And fracture belt is identified with: being extended linearly
Ribbon, the low MIC value of beading it is abnormal, have the low MIC value of cricoid feature abnormal.
Further, the calculating formula of the MIC value is as follows:
In formula, xy < B (n) refers to that mesh segmentation fineness is less than B (n)；Wherein M (D)X, yIt is characterized matrix.
Further, the M (D)X, yExpression formula it is as follows:
In formula, I*(D, x, y) is the maximum mutual information in given x column, y row situation.
The invention has the benefit that
(1) present invention introduces the MIC in big data analysis excavation, are calculated between grid cell and observation data before inverting
MIC value, and as the reliability for promoting inversion result from constraint condition；
(2) restricted model is also replaced with constraint nuclear matrix by the present invention, solves indirect problem in terms of saving using LSQR algorithm
It is counted as this.
(3) rule between two attribute data is excavated by calculating the MIC value between density and magnetism, to reach fast
The purpose of fast joint interpretation.
Detailed description of the invention
Fig. 1 is step schematic diagram of the invention；
Fig. 2 is the synthetic model structure chart of the embodiment of the present invention；
Fig. 3 is the inversion result figure that traditional algorithm is utilized in the embodiment of the present invention；
Fig. 4 is that the inversion result figure of the inversion method in embodiment 2 is utilized in the embodiment of the present invention；
Fig. 5 is certain mining area gravity 3-d inversion result schematic diagram in the embodiment of the present invention；
Fig. 6 is the MIC value plan view and its explanation figure of the density magnetic in the embodiment of the present invention；Wherein a:MIC value plane
Scheme, grey indicates that MIC value is big in figure, and black indicates that MIC value is small；B: Interpretation of Fracture Structures figure；
Fig. 7 is the step schematic diagram of inverting of the present invention.
Specific embodiment
With reference to the accompanying drawing and specific embodiment does further explaination to the present invention.
Embodiment:
The present embodiment provides a kind of heavy magnetic from constraint 3-d inversion and joint interpretation method, as shown in Figure 1, specific steps are such as
Under:
Sliding-model control is carried out to the underground space of target area, subdivision is multiple grid cells；Calculate separately each net
Lattice unit distinguishes the MIC value of gravity and magnetic method data using corresponding MIC value and depth weighted coefficient as constraint condition
Form the constraint nuclear matrix certainly of gravity and magnetic method inverting；Gravity and magnetic method inversion problem are solved respectively by LSQR method, are obtained
Gravity and magnetic method inversion result；According to gravity and magnetic method inversion result, the density and magnetism of each grid cell are calculated；Calculate edge
The MIC value between density and magnetism on depth direction carries out analysis and geologic interpretation according to the planar distribution of MIC value.
To promote the reliability of inversion result, save Inversion Calculation cost and quickly carry out joint interpretation to be in the present embodiment
Purpose, be introduced into big data analysis excavate in MIC (maximum information number), as from constraint condition to promote inversion result
Restricted model is replaced with constraint nuclear matrix by reliability, is solved indirect problem using LSQR algorithm to save calculating cost, is passed through meter
The MIC value between density and magnetism is calculated to excavate the rule between two attribute data, to achieve the purpose that fast joint is explained.
Finally, by compared with the calculating cost of traditional method, synthetic model inversion result and practical application effect shows this
The superperformance of patent of invention.
As shown in Figure 1, specific inversion step is as follows:
(1) M grid cell is turned to by the underground space is discrete；
(2) nuclear matrix elements A (i, j) and MIC are calculatedj；
(3) constraint nuclear matrix A is calculated*, wherein A*(i, j)=A (i, j) lj
(4) discomfort is solved based on LSQR algorithm and determines A*m*=d, according to L-curveTurn
Point returns to the solution of corresponding the number of iterations；
(5) grid cell recycles, according to formulaReverse model value exports solving result m.
And it is specifically as follows according to inversion result joint interpretation method:
(1) according to each horizontal grid unit of weight magnetic inverting, its density and magnetism on depth direction is taken, is calculated
MIC value；
(2) finally using the plane coordinates of horizontal grid unit and MIC value at figure, geologic body and rift structure are divided.
Effect calculation is carried out according to the above method, wherein between first more traditional Tikhonov regularization and LSQR algorithm
Difference.
As shown in fig. 7, showing the constraint inversion algorithm effect certainly in this patent with a synthetic model, it is different by two
Normal body composition, as shown in figure 3, its left side anomalous body remanent magnetization is 0.8A/m, right side anomalous body remanent magnetization is
1A/m.Assuming that the inclination angle (45 °) in total magnetization intensity direction and opposite X-axis drift angle (50 °) are consistent with earth's magnetic field.Data are added
Then 10% Gaussian noise carries out Inversion Calculation from constraint inversion algorithm using in traditional inversion algorithm and this patent.
By Fig. 4 and Fig. 5 as it can be seen that the solving result of two kinds of inversion algorithms differs greatly, in terms of being mainly manifested in following two:
First, the magnetization range difference solved is big, traditional inversion algorithm solves range between -0.1~0.4A/m (Fig. 4), and
Range between -0.1~1A/m (Fig. 5) is solved from constraint inversion algorithm, the magnetization range of the latter and synthetic model is more
It is close；Second, have differences on imaging effect, traditional inversion algorithm result is relatively fuzzyyer, especially deep be difficult to identify that by
Two anomalous bodys composition, inverting exception bottom be (Fig. 4) of diverging, from constraint inversion algorithm result then obviously with synthetic model more
Adjunction is nearly (Fig. 5), can identify the position of true anomalous body easily according to inversion result.In short, constraining in this patent certainly
The reliability of inversion algorithm solving result is substantially better than traditional inversion algorithm.
Tikhonov regularization and matrix in block form LSQR method calculate Cost comparisons
Wherein: (N × M) representing matrix order, N are data volume, and M is model value；K is the number of iterations of LSQR method, generally
For k < < min (M, N)；Space needed for amount of storage does not include matrix inversion；O indicates time or space complexity；- it is not relate to
And.
Tradition is given in upper table based on Tikhonov regularization and calculation amount involved in this patent inversion algorithm and is deposited
Store up space.Wherein, space complexity needed for the present embodiment inversion algorithm is only O (2M+2N), and time complexity is only O (2kMN).
Since under normal circumstances, the number of iterations k of LSQR algorithm is much smaller than data volume N and model value M, therefore, just compared to Tikhonov
Then change, the inversion algorithm in the present embodiment saves a large amount of memory spaces and calculates the time.
Assuming that surveying the scale that area's grid data is 100 × 100, the three-dimensional grid that model is 100 × 100 × 50, LSQR is calculated
Method the number of iterations is 1000 times.Then the calculation amount of this patent inversion algorithm is about a ten thousandth of conventional Ti khonov regularization.
If data are stored with double precision, conventional Ti khonov regularization needs amount of storage in about 2TB, and this patent inversion algorithm only needs about
Amount of storage in 100MB is the former 1/20th.As it can be seen that the Inversion Calculation task of so scale data, anti-using this patent
Algorithm is just achievable on a common computer.
Then the method in the present embodiment is particularly applicable in practical mineral exploration, concrete application is as follows:
By taking ten thousand gravimetric data of certain mining area 1:2.5 as an example, to show this patent to the effect for looking for latent Pb- Zn orebody.Lead zinc antimony
Mine is the largest polymetallic deposit in somewhere, and ore bodies are stored in lower stratum, mainly by nearly north-south (torsion) property angle of elevation
Normal fault control is spent, Ore-control fault totality west is inclined.Studies have shown that although Pb-Zn deposits (change) body shows as high density, but due to mine
In fractured zones, highdensity mine (change) body is abnormal often to be flooded by the fractured zones of low-density body preservation extremely,
Corresponding surface observation GRAVITY ANOMALIES, which often shows, to be negative.Therefore, the low of nearly north-south is disclosed by gravity 3-d inversion
Density anomaly position can reach the purpose for looking for mine indirectly.Totally 2100 the points of measurement evidences, a grid cell more than 140,000, common
It is calculated on laptop (memory 8GB, double-core, processor: Intel i5-6300HQ, dominant frequency 2.30GHz), altogether time-consuming
18min, fitting mean square error are 0.133mGal, are met the requirements.
As shown in fig. 6, by three-dimensional density imaging results as it can be seen that known No. V ore body to show as the low-density inclined of west different
Often, and the low-density is abnormal is walking also consistent with No. V ore body upwards, and it is different to illustrate to move towards nearly north-south, the low-density of tendency westwards
Often with there is Exploration guide effect.No. V ore body southeast side there are similar low-density exception, the area is thought in conjunction with other data
With ore-searching potential.It is verified for this purpose, having laid corresponding drilling, head, which is bored, sees lead Zn Cr coating mine in 183~189m of depth
Body, a series of subsequent drillhole validations work well, and ore average grade is newfound Ⅹ No. V mines in area up to 11% or more
Body, reserves realize economic results in society up to 1,000,000,000 yuans up to 300,000 tons.In addition, No. V ore body and Ⅹ No. V ore bodies it
Between the low-density with close ellipse it is abnormal, other data show that the low-density is low electric conductivity extremely, thus it is speculated that for middle acid
Property rock mass, No. V ore body and Ⅹ No. V ore bodies are respectively positioned near rock mass, this is consistent with area's magmatic hydrothermal metallogenesis.Above-mentioned reality
Data inversion effect in border illustrates that the three-dimensional inversion algorithm of constraint certainly in the present embodiment has good reliability, accuracy and answers
Use prospect.
It is three-dimensional through this embodiment to obtain underground from constraint inversion algorithm by taking ten thousand gravity and magnetic data of certain area Kuang Ji 1:5 as an example
After density and magnetism, according to each horizontal grid unit, its density and magnetism on depth direction is taken, is calculated between the two
MIC value is then plotted into grayscale image, as shown in fig. 7, to divide geologic body or geological structure.
In Fig. 7, solid black lines are Cuona County, the gneiss arched roof boundary, hole (upper Detachment Zone) determined according to geologic information, solid line
For the band that broken determined according to geologic information.As seen from Figure 7, the MIC value of Cuona County hole gneiss arched roof is totally larger and uniform, encloses
Existing significantly around arched roof has cyclic annular MIC value low with the ribbon, the beading that extend linearly abnormal.Wherein, around arched roof
The cyclic annular abnormal arched roof boundary position determined with geologic information of low MIC value is almost the same；Other local linear extensions or string
It is abnormal almost the same with known fracture position that pearl is distributed low MIC value；In addition, also inferred some buried faults, these deductions
The local location of fracture has obtained the confirmation of other data.It proves to know in the present embodiment using the MIC between density and magnetism
It is feasible and reliable for not reaching quickly division geologic body and rift structure.
The present invention is not limited to above-mentioned optional embodiment, anyone can show that other are each under the inspiration of the present invention
The product of kind form.Above-mentioned specific embodiment should not be understood the limitation of pairs of protection scope of the present invention, protection of the invention
Range should be subject to be defined in claims, and specification can be used for interpreting the claims.
Claims (8)
1. a kind of heavy magnetic constrains 3-d inversion and joint interpretation method certainly, it is characterised in that: the following steps are included:
G1. carrying out sliding-model control cutting to the underground space of objective area first is multiple grid cells；
G2. each grid cell is calculated separately for the MIC value of gravity and magnetic method data, by corresponding MIC value and depth weighted
Coefficient is used as from constraint function, is respectively formed the constraint nuclear matrix certainly of gravity and magnetic method inverting；
G3. gravity and magnetic method inversion problem are solved by regularization method respectively, obtain the inversion result of gravity and magnetic method；
G4. according to gravity and magnetic method inversion result, the density and magnetism of each grid cell are calculated；
G5. calculate the MIC value between the density and magnetism on depth direction again, and according to the planar distribution of MIC value into
Row analysis and geologic interpretation.
2. a kind of heavy magnetic according to claim 1 is from constraining inversion method, it is characterised in that: because by mesh in the step G2
The underground space in mark area is divided into multiple grid cells, therefore inverse model is as follows:
Am=d
In formula: A is nuclear matrix；M is vector to be solved, i.e. density or magnetism；D is observation data vector.
3. a kind of heavy magnetic according to claim 1 or 2 constrains 3-d inversion and joint interpretation method certainly, it is characterised in that:
It is as follows from constraint function expression formula in the step G2:
D=DMICDdepth
In formula: the DMIC=diag { 1/MIC1,1/MIC2,Λ,1/MICM, and MICjFor the MIC value of corresponding grid cell；
The Ddepth=diag { 1/ (z1)β/2,1/(z2)β/2,Λ,1/(zM)β/2, zjFor the center buried depth of corresponding grid cell.
4. a kind of heavy magnetic according to claim 3 constrains 3-d inversion and joint interpretation method certainly, it is characterised in that: described
Inverse model in step G2 is as follows:
A*m*=d
In formula: the A*=AD-1；The m*=Dm.
5. a kind of heavy magnetic according to claim 4 constrains 3-d inversion and joint interpretation method certainly, it is characterised in that: described
It is calculated in step G3 using LSQR canonical algorithm.
6. a kind of heavy magnetic according to claim 5 constrains 3-d inversion and joint interpretation method certainly, it is characterised in that: described
Specific step is as follows by step G2-G4:
Nuclear matrix elements A (i, j) and MIC are calculated firstj；
Then constraint nuclear matrix A is calculated*, according to A*(i, j)=A (i, j) ljA is calculated*, wherein
Discomfort, which is solved, based on LSQR algorithm determines A*m*=d, according to L-curveInflection point, return pair
Answer the solution of the number of iterations；
Grid cell circulation, according to formulaReverse model value exports solving result m.
7. according to a kind of described in any item heavy magnetic of claim 4-6 from constraint 3-d inversion and joint interpretation method, feature
Be: specific step is as follows by the step G5:
(5.1) according to each horizontal grid unit of weight magnetic inverting, its density and magnetism on depth direction is taken, calculates MIC
Value；
(5.2) finally using the plane coordinates of horizontal grid unit and MIC value at figure, geologic body and rift structure are divided.
8. a kind of heavy magnetic according to claim 7 constrains inversion method certainly, it is characterised in that: the M (D)X, yExpression formula
It is as follows:
In formula, I*(D, x, y) is the maximum mutual information in given x column, y row situation.
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| CN110333548A (en) * | 2019-07-27 | 2019-10-15 | 吉林大学 | A kind of high-resolution inversion of Density method based on the abnormal weight function of normalization |
| CN110687610A (en) * | 2019-09-19 | 2020-01-14 | 长安大学 | Gravity and magnetic data correlation analysis-based field source positioning and attribute identification method |
| CN110687610B (en) * | 2019-09-19 | 2021-03-19 | 长安大学 | Gravity and magnetic data correlation analysis-based field source positioning and attribute identification method |
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| CN112528546B (en) * | 2020-12-29 | 2022-02-15 | 中国地质大学（武汉） | Gravity and magnetic data three-dimensional forward and backward modeling method for unstructured grid |
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